Know your options for managing checked exceptions in Java 8’s functional approach.
Electronic waste is an economic and environmental problem, but citizen scientists can take action by using harvesting sensor from discarded electronics.
AI Needs Ethics, Automotive-Grade Linux, Drawing Clocks, and Facial Recognition
How to construct inquiries that will result in good, useful data.
Learn how to add big data to your organization's business processes.
Five questions for Josiah Dykstra on techniques to expose and invalidate misleading claims.
Andrew Ng shares his thoughts on where the biggest opportunities in AI may lie.
Ruchir Puri addresses the opportunities and challenges of AI for business and focuses on what's needed to scale AI across the breadth of enterprises.
AI Conference chairs Ben Lorica and Roger Chen reveal the current AI trends they've observed in industry.
Watch highlights covering artificial intelligence, machine learning, applied deep learning, and more. From the Artificial Intelligence Conference in San Francisco 2017.
Peter Norvig speaks with Abu Qader, the 18-year-old CTO of GliaLab who taught himself machine learning and launched an AI company for breast cancer diagnostics.
Rana el Kaliouby lays out a vision for an emotion-enabled world of technology.
A deep dive into Uber's engineering effort to optimize geospatial queries in Presto.
Understanding gRPC in the dawn of microservices.
Building convnets from scratch with TensorFlow and TensorBoard.
The O'Reilly Podcast: Dave Cassel on building a unified enterprise database to store and query any type of data.
See examples of the many traps you can fall into if you use off-the-shelf anomaly detection techniques.
Learn the difference between live and streaming anomaly detection systems and how to address the challenges different data velocities pose.
Learn about some of the common issues you will encounter when developing algorithms for a modern anomaly detection system.
The O’Reilly Data Show Podcast: Ion Stoica and Matei Zaharia explore the rich ecosystem of analytic tools around Apache Spark.
A deep dive into startup TuSimple’s use of Apache MXNet.
The O’Reilly Security Podcast: Shifting secure code responsibility to developers, building secure software quickly, and the importance of changing processes.
Exciting new genetic testing technology has improved the speed and accuracy of cancer diagnosis.
Data capture, management, and analysis builds a bridge between design, user experience, and business relevance.
Learn some of the benefits of using real-time processing of data for some use cases.
Learn to identify problems that may indicate data team dysfunction.
Learn about the four major image and object formats accepted by Figma - and three ways to import them.
6 lessons learned to get a quick start on productivity.
Learn about Figma's layers area – where you control individual objects, images, and text – and avoid making overly complex Figma documents.
Learn about Figma's Frame tool — then use it to define the correct workspace for the prototype of your website, tablet app, or smart phone app.
A look at the Layer API, TFLearn, and Keras.
Artificial intelligence is emerging as a creative force; in the process, it reveals something of itself.
Turning abstract AI into real business solutions.
Sound design should not be an afterthought at the end of a design process.
The O’Reilly Programming Podcast: A look at what’s new in Java 9 and Spring 5.
Building a production-grade real-time image classification system.
Learn to install Ant software - and get it ready to integrate with Jenkins - by using the Jenkins automatic installation feature.
Applications of CNNs for real-time image classification in the enterprise.
Learn how to automate Jenkins continuous integration projects with Apache Ant, a popular build tool for developing software.
Learn how to set up an external job within Jenkins and manage its execution using the Jenkins command line interface.
Are we out of the woods?
Five questions for Bryan Liles on the complexities of tracing, recommended tools and skills, and how to learn more about monitoring.
Generate new images and fix old ones using neural networks.
Why machine learning needs real-time data infrastructure.
Learn how to use IBM Watson's APIs and natural language understanding to extract information about people and companies from news articles.
Learn how to use IBM Watson's APIs and natural language understanding to analyze the tone of social media posts like tweets.
Steve Portigal shares what can go wrong in the real world.
The O’Reilly Data Show Podcast: Kenneth Stanley on neuroevolution and other principled ways of exploring the world without an objective.
There’s beauty in biology—and the biotech industry is ready to make a move
Understanding the impact and expanding influence of DevOps culture, and how to apply DevOps principles to make your digital operations more performant and productive.
The O’Reilly Security Podcast: The open-ended nature of incident response, and how threat intelligence and incident response are two pieces of one process.
Help PMs navigate the challenges that will test them as they learn about and navigate your organization.
Building and tuning traffic management for large web-scale applications.
Nadia Eghbal explores how money can support open source development without changing its incentives.
Andrew Odewahn explains how O’Reilly Media applied the Jupyter architecture to create the next generation of technical content.
Brett Cannon looks at how healthy expectations can maintain a balanced relationship between open source users and project maintainers.
Jeremy Freeman describes a growing ecosystem of scientific solutions, many of which involve Jupyter.
William Merchan shares fundamental trends driving the adoption of Jupyter and its deployment in large organizations.
Lorena Barba explores how we can build a capacity to support reproducible research into the design of tools like Jupyter.
Five questions for Charles Givre on building effective security analytics programs.
Wes McKinney makes the case for a shared infrastructure for data science.
Rachel Thomas shares her experience using Jupyter notebooks to help students understand deep learning through experimentation.
Peter Wang talks about the co-evolution of Jupyter and Anaconda and looks at what’s needed to sustain an open and innovative future.